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| Section | Weight | Objectives |
|---|---|---|
| Integrate and Extend Agents in Copilot Studio | 40-45% | - Build advanced agent solutions
|
| Plan and Configure Agent Solutions | 30-35% | - Plan agent solutions
|
| Test and Manage Agents | 20-25% | - Monitor and manage agent solutions
|
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NEW QUESTION # 59
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear on the review screen.
An agent uses a flow that calls an external service which can occasionally fail or time out.
When a failure occurs, the agent must meet the following requirements:
- Must not terminate silently.
- Must send a notification containing the error details.
You need to configure the agent flow so that failures are handled in a controlled and predictable way.
Solution: Retry the failing action without handling failure.
Does the solution meet the goal?
Answer: A
Explanation:
Correct:
* Configure run after conditions for failure paths.
You should configure the "Run after" conditions in Power Automate (the underlying flow engine) to handle these failures in a controlled and predictable way.
By default, a cloud flow step only runs if the previous step is successful. If your external service fails or times out, all subsequent steps will normally skip, causing the flow to fail silently from the perspective of the Copilot Studio agent.
How to Configure the Flow for Failure Handling
To meet your requirements, you need to create a parallel or sequential failure path using the following steps:
1. Add your Notification Action
2. Configure "Run After" Settings
Incorrect:
* Retry the failing action without handling failure.
* Send a notification with relevant error details.
Reference:
https://www.matthewdevaney.com/3-power-automate-error-handling-patterns-you-must-know/
NEW QUESTION # 60
Case Study 1 - Blue Yonder Airlines
Background
Blue Yonder Airlines is a global carrier headquartered in Los Angeles, California, operating domestic and international flights. The company serves millions of passengers annually through its website, mobile app, and call centers. To improve customer service efficiency and reduce call center volume, Blue Yonder is deploying an AI agent in Microsoft Copilot Studio.
The agent will handle customer inquiries across multiple channels - web chat, mobile app, and Microsoft Teams (for internal support staff). It will answer questions, retrieve data from enterprise systems, and escalate to human agents when needed.
The project is led by a cross-function team:
- Product manager: Defines requirements and success metrics.
- Lead agent author: Designs topics, intents, and generative behavior.
- Flow designers: Build agent flows and integrations.
- IT/security and compliance: Oversees identity, data protection, and Responsible AI (RAI) compliance.
Current environment
Channels
Public website: Embedded web chat
Mobile app: In-app chatbot
Microsoft Teams: Internal support agent access
Identity and access
Customers: Anonymous access for general inquiries (e.g., flight status, baggage policy).
Authentication is required for personal data access (e.g., bookings, loyalty points).
Internal staff: Authenticate via Microsoft Entra ID.
Data sources
Reservation and Ticketing System (internal): REST API, no prebuilt connector with custom enterprise database.
Flight Status and Weather APIs (external): REST APIs with API keys.
Customer Support Knowledge Base: SharePoint library with PDFs and policy documents.
Loyalty Program Data: Stored in Dynamics 365 and Dataverse.
Travel Advisory Content: Uses REST API with partner services.
Integration mechanisms
Custom connectors must be used for internal APIs that lack prebuilt connectors.
HTTP request nodes may be used for lightweight external APIs.
Knowledge sources must be used for unstructured content.
Agent flows must be used to encapsulate reusable logic (e.g., rebooking).
Business requirements
Omnichannel support
Deploy the agent across web, mobile, and Teams with a consistent user experience. The Teams deployment must also support internal staff.
Self-service capabilities
The agent must handle common inquiries such as:
- Flight status
- Booking and rebooking
- Loyalty program questions
- Travel policies and baggage rules
Human escalation
If the agent cannot resolve an issue or the user requests help, it must:
- Escalate to a human agent.
- Transfer the conversation transcript and relevant context.
- Redact any sensitive personal data before escalation.
Knowledge integration
The agent must use scalable methods for knowledge integration and must not rely on manually authored Q&A topics for each document.
Performance metrics
First-contact resolution: +25%
Tier-1 call deflection: โฅ20%
Response time: 90% of queries answered within 30 seconds
Accuracy: โฅ95% for known FAQs
CSAT: โฅ85% for AI-handled interactions
Technical requirements
Platform constraints
No custom code is permitted; only Copilot Studio's built-in tools may be used.
All backend logic must be implemented using agent flows.
Markdown must be used for formatting (e.g., bold, bullet points); HTML is not supported.
Authentication
Sign-in is required for personal data access.
Anonymous access is allowed for general inquiries.
User identity must be used for data access; shared or builder credentials must not be used.
Compliance and security
Power Platform DLP policies must be enforced to block unauthorized data flows.
Responsible AI content moderation filters must be enabled.
Prompt modifications must be added to enforce tone, disclaimers, and refusal behavior.
Disclaimers must be applied consistently across all generative responses. Manual edits to individual topics must be avoided.
Monitoring and maintenance
All conversations and actions must be logged for auditing.
Weekly reviews of transcripts and metrics must be conducted.
Topics, flows, and knowledge sources must be updated as policies or systems evolve.
Issues and constraints
API rate limits: External APIs (e.g., flight status) have usage limits. Agent flows must handle retries and caching to avoid exceeding quotas.
Knowledge base limits: Copilot Studio has limits on the number and size of indexed documents.
Large files must be split or summarized.
Generative answer risks: Generative responses must be constrained to avoid policy violations.
Prompt modifications and filters must be used to enforce tone, safety, and compliance.
User input variability: Users phrase questions in diverse ways. Topics must include varied trigger phrases and fallback handling.
Authentication UX: The agent must clearly explain when sign-in is required and handle transitions smoothly across channels.
Problem statement
Blue Yonder Airlines must deploy a secure, scalable, and policy-compliant AI agent using Microsoft Copilot Studio. The agent must deliver accurate, helpful, and safe responses across multiple channels, integrate with enterprise systems, and support both anonymous and authenticated users. It must adhere to strict data protection and Responsible AI standards while improving customer service efficiency and satisfaction.
You need to ensure that every AI-generated response from the agent in Copilot Studio includes a disclaimer that complies with the company's security and governance policies.
Which two actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
Answer: B,E
Explanation:
[B]
Using prompt modification in the Generative Answers node settings is an excellent and highly effective strategy for embedding compliance disclaimers into your agent's responses.
[A]
Adding a mandatory disclaimer to your greeting message is the best practice for agent governance. You can enforce this by configuring your Greeting System Topic and adding formal
"Output Rules" to the agent's core instructions.
Reference:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/nlu-boost-node
https://www.reddit.com/r/copilotstudio/comments/1pje5fy/how_do_you_handle_ai_disclaimers_in
_copilot/
NEW QUESTION # 61
A company uses multiple Copilot Studio agents that perform specialized tasks.
You need to configure a Copilot Studio agent in your environment to connect to an external agent.
What should you do?
Answer: A
Explanation:
You should provide the A2A endpoint information for the target agent.
When configuring a Microsoft Copilot Studio agent to connect to an external agent over the Agent2Agent (A2A) protocol, providing the target agent's public communication endpoint URL is the mandatory step required to establish the connection.
Reference:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/add-agent-agent-to-agent
NEW QUESTION # 62
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear on the review screen.
A team is implementing ALM for agents in Copilot Studio across multiple environments.
The team requires a consistent way to manage and transport agent assets.
You need to recommend a solution that supports creation and use of ALM scenarios for agents in Copilot Studio.
Solution: To export, import, and manage agents between environments, you need to create and use a custom solution.
Does the solution meet the goal?
Answer: A
Explanation:
Correct:
* Builders can change environment variable values directly in Copilot Studio to complete ALM configuration without administrative tools.
builders can change environment variable values directly during the solution import process to complete Application Lifecycle Management (ALM) configurations.
Native ALM in Copilot StudioMicrosoft Copilot Studio embeds native solution management capabilities directly within the app authoring environment. This design minimizes the reliance on standalone administrative portals or complex external tools for standard deployment tasks.
The Import Process: When you transport your agent by importing its containing solution into a target downstream environment (such as Test or Production), Copilot Studio prompts you for environment-specific parameters.
Modifying Values: Builders can update the "current value" of environment variables right inside the import wizard panel. Alternatively, you can let them fall back to pre-defined default parameters.
Supported Scenarios: This inline editing mechanism is commonly used to dynamically update variables tied to external resources, such as changing SharePoint URLs or public website links used for generative AI knowledge grounding between sandbox and live states.
Incorrect:
* Publishing an agent to a channel is the required ALM container for transporting agents between environments.
* Publishing an agent to a channel is not the required or correct ALM container for transporting agents between environments.
* To export, import, and manage agents between environments, you need to create and use a custom solution.
Reference:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/guidance/alm
NEW QUESTION # 63
An agent in Copilot Studio already exists in a development environment.
You need to prepare the agent so it can be moved to a production environment by using the supported solution-based approach.
You need to create an exportable package that contains the existing agent.
Which two actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
Answer: D,E
NEW QUESTION # 64
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